The proposed architecture for the Single-task approach lends from popular and extensively studied architectures in the field of Handwritten Text Recognition [1]}, [2]}, [3]}.
Similarly to typical HTR architectures, our system is consisted of an Optical Model (CNN) topped by a context-aware Sequential Model (LSTM).
However, contrary to typical flattening operations, our approach assumes a column-wise max-pooling operation to convert the optical output into a sequence of features, as requested by the Sequential Model.
The overview of the proposed single-task baseline is depicted in Figure REF .
